Mechanisms and Dynamics of Carbapenem Resistance in Escherichia coli

Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 998
Mechanisms and Dynamics of Carbapenem Resistance in Escherichia coli
MARLEN ADLER
ISSN 1651-6206 ISBN 978-91-554-8950-2 urn:nbn:se:uu:diva-221432
Dissertation presented at Uppsala University to be publicly examined in B42, BMC, Husargatan 3, Uppsala, Thursday, 5 June 2014 at 09:00 for the degree of Doctor of Philosophy (Faculty of Medicine). The examination will be conducted in English. Faculty examiner: Ph. D. Josep Casadesús (University of Seville).
Abstract Adler, M. 2014. Mechanisms and Dynamics of Carbapenem Resistance in Escherichia coli. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 998. 51 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-554-8950-2.
The emergence of extended spectrum β-lactamase (ESBL) producing Enterobacteriaceae worldwide has led to an increased use of carbapenems and may drive the development of carbapenem resistance. Existing mechanisms are mainly due to acquired carbapenemases or the combination of ESBL-production and reduced outer membrane permeability. The focus of this thesis was to study the development of carbapenem resistance in Escherichia coli in the presence and absence of acquired β-lactamases. To this end we used the resistance plasmid pUUH239.2 that caused the first major outbreak of ESBL-producing Enterobacteriaceae in Scandinavia.
Spontaneous carbapenem resistance was strongly favoured by the presence of the ESBL- encoding plasmid and different mutational spectra and resistance levels arose for different carbapenems. Mainly, loss of function mutations in the regulators of porin expression caused reduced influx of antibiotic into the cell and in combination with amplification of β-lactamase genes on the plasmid this led to high resistance levels. We further used a pharmacokinetic model, mimicking antibiotic concentrations found in patients during treatment, to test whether ertapenem resistant populations could be selected even at these concentrations. We found that resistant mutants only arose for the ESBL-producing strain and that an increased dosage of ertapenem could not prevent selection of these resistant subpopulations. In another study we saw that carbapenem resistance can even develop in the absence of ESBL-production. We found mutants in export pumps and the antibiotic targets to give high level resistance albeit with high fitness costs in the absence of antibiotics. In the last study, we used selective amplification of β-lactamases on the pUUH239.2 plasmid by carbapenems to determine the cost and stability of gene amplifications. Using mathematical modelling we determined the likelihood of evolution of new gene functions in this region. The high cost and instability of the amplified state makes de novo evolution very improbable, but constant selection of the amplified state may balance these factors until rare mutations can establish a new function.
In my studies I observed the influence of β-lactamases on carbapenem resistance and saw that amplification of these genes would further contribute to resistance. The rapid disappearance of amplified arrays of resistance genes in the absence of antibiotic selection may lead to the underestimation of gene amplification as clinical resistance mechanism. Amplification of β- lactamase genes is an important stepping-stone and might lead to the evolution of new resistance genes.
Keywords: carbapenem, antibiotic resistance, fitness cost, ESBLs, penicillin-binding proteins, gene amplification
Marlen Adler, Department of Medical Biochemistry and Microbiology, Box 582, Uppsala University, SE-75123 Uppsala, Sweden.
© Marlen Adler 2014
ISSN 1651-6206 ISBN 978-91-554-8950-2 urn:nbn:se:uu:diva-221432 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-221432)
Not everything that counts can be counted, and not everything that
can be counted counts.
List of Papers
This thesis is based on the following papers, which are referred to in the text by their Roman numerals.
I Adler M, Anjum M, Andersson DI, Sandegren L. (2012) Influence of
acquired β-lactamases on the evolution of spontaneous carbapenem resistance in Escherichia coli. J Antimicrob Chemother 68: 51-59
II Tängdén T, Adler M, Cars O, Sandegren L, Löwdin E. (2013) Fre-
quent emergence of porin-deficient subpopulations with reduced car- bapenem susceptibility in extended-spectrum-β-lactamase-producing Escherichia coli during exposure to ertapenem in an in vitro pharma- cokinetic model. J Antimicrob Chemother 68(6):1319–1326
III Adler M, Anjum M, Andersson DI, Sandegren L. Mutations in PBP2,
PBP3 and AcrB contribute to high-level carbapenem resistance in Escherichia coli. Manuscript
IV Adler M, Anjum M, Berg OG, Andersson DI, Sandegren L. (2014)
High fitness costs and instability of gene duplications reduce rates of evolution of new genes by duplication-divergence mechanisms. Mol Biol Evol doi:10.1093/molbev/msu111
Reprints were made with permission from the respective publishers.
Contents
β-lactam antibiotics ...................................................................................... 14   Carbapenems ............................................................................................ 18  
β-lactam resistance ....................................................................................... 20   Role of outer membrane proteins in resistance ........................................ 20   Inactivation by β-lactamases .................................................................... 22   Inactivation by Carbapenemases .............................................................. 25  
ESBL plasmid pUUH239.2 .......................................................................... 26   Gene duplication and amplification .............................................................. 28  
Dynamics ................................................................................................. 28   Mechanism of formation and loss of GDA .............................................. 30   Evolution of new genes by duplication-divergence ................................. 30  
Escherichia coli and Klebsiella pneumoniae as pathogens .......................... 32  
Present Investigations ........................................................................................ 33   ESBL-plasmid influences evolution of carbapenem resistance .................... 33   Ertapenem resistance due to pUUH239.2 in a pharmacokinetic model ....... 34   Altered PBPs and drug efflux cause high-level carbapenem resistance ....... 35   Cost and instability of GDA limit evolution of new genes .......................... 36   Concluding Remarks .................................................................................... 38  
Future Perspectives ........................................................................................... 39  
Deutsche Zusammenfassung ............................................................................. 41  
ARDB Antibiotic resistance gene database bp Base pair DNA Deoxyribonucleic acid E. coli Escherichia coli ESBL Extended spectrum β-lactamase EUCAST European committee on antimicrobial susceptibility testing GDA Gene duplication and amplification HGT Horizontal gene transfer HMM High-molecular mass IAD Innovation-amplification-divergence IS Insertion sequence K. pneumoniae Klebsiella pneumoniae kb Kilo base pair LMM Low-molecular mass Mb Mega base pair MIC Minimal inhibitory concentration P. aeruginosa Pseudomonas aeruginosa PBP Penicillin-binding protein PFGE Pulsed-field gel electrophoresis qRT-PCR Quantitative real-time polymerase chain reaction rhs Recombination hot spot RNA Ribonucleic acid S. typhimurium Salmonella enterica serovar Typhimurium strain LT2 S. aureus Staphylococcus aureus S. cattleya Streptomyces cattleya SIR Sensitive-intermediate-resistant S. pneumoniae Streptococcus pneumoniae
9
Introduction
The discovery of antibiotics is often referred to as the greatest achievement of the 20th century. Together with the implications of germ theory by Louis Pasteur (1864), antibiotics are one of the main contributors to the increased human life expectancy of today. The introduction of antibiotics revolution- ized medicine and we are relying on antibiotic therapy for treatment of inju- ries and minor infections, but also for deep surgery, transplantation, chemo- therapy, neonatal care and prosthetic surgery. However, resistance to antibi- otic exposure was observed already before the clinical introduction of these compounds and quickly developed into a serious health care problem. We underestimated the genetic capacity of microbes to evolve and spread re- sistance genes among themselves and were not aware of the vast amount of resistance genes that are naturally present after millions of years of microbial evolution (more than 23,000 resistance genes, ARDB – antibiotic resistance gene database, http://ardb.cbcb.umd.edu/). Bacteria benefitted from the mis- use of antibiotics, not only as over the counter drugs but also for growth promotion in livestock, and we witnessed evolution at its best during less than 100 years of antibiotic therapy. Fortunately, not all predicted resistance genes found their way into the genomes of potential pathogenic bacteria or have spread sufficiently to reach epidemic magnitudes. It is therefore imper- ative to describe, understand and predict microbial resistance mechanisms to limit their spread and develop strategies to prolong the life span of antibiot- ics.
In this thesis I studied the mechanisms by which Escherichia coli can de- velop resistance to carbapenems, a group of last resort β-lactam antibiotics aimed for treatment of otherwise multi-resistant bacteria, in the laboratory and at concentrations typically found in patient serum during treatment. De- tailed studies of a frequent bacterial adaptation mechanism provided addi- tional understanding of the evolution of new resistance genes. The results presented in this thesis may be important to decide antibiotic treatment re- gimes and also give insights into bacterial evolution in general.
10
Antibiotics Antibiotics (Greek anti, “against”, bios, “life”) are chemicals that are used clinically to treat bacterial infections. Most antibiotics are initially derived from natural substances produced by microorganisms such as bacteria and fungi to inhibit the growth of other microbes. This effect can be by growth inhibition (bacteriostatic) or killing of other microbes (bactericidal). In addi- tion to the great number of naturally occurring antibiotics identified, semi- synthetic drugs have been developed through chemical modification of natu- ral products. Natural and semi-synthetic products make up the largest pro- portion of antibiotics in therapeutic use today, but three classes of truly syn- thetic antibiotics also exist: sulfa drugs, quinolones and oxazolidinones. Depending on their chemical characteristics, antibiotics exert their effect on differing sets of bacterial species. Narrow-spectrum antibiotics affect a lim- ited range of bacterial species, whereas broad-spectrum antibiotics affect a wide range of microbes including Gram-positive and Gram-negative bacte- ria. The development of antimicrobial drugs has greatly enhanced the control of infectious diseases and facilitated the improvement of advanced invasive medicine.
The most important characteristic to predict the outcome of antimicrobial therapy is the specific antibiotic concentration that is necessary to inhibit growth of a pathogen. This is called the minimal inhibitory concentration (MIC) and can be determined by three methods: i) In disc diffusion tests, antibiotics diffusing from a paper disc cause a zones of growth inhibition and the size of this zone can be compared to reference strains or related to treatment outcome. ii) Growth of bacteria in broth with serial dilutions of antibiotics can be used to determine the MIC (Andrews, 2001). iii) Commer- cially available ‘Etests’ offer a gradient of antibiotic concentration on a plas- tic strip. The antibiotic diffuses off the strip causing a zone with growth inhibition. The inhibiting concentration can be read from the printed scale as the lowest concentration that inhibits growth. Static or kinetic time-kill ex- periments cannot be used to measure the MIC, but are useful to study the effects of stable or varying antibiotic concentrations on bacterial survival. The so-called SIR-system (sensitive-intermediate-resistant) uses two empiri- cal determined antibiotic concentrations to predict the outcome of antimi- crobial therapy. These breakpoint concentrations are called clinical break- points. The outcome of antibiotic treatment is unclear if the MIC of the in- fecting bacterium exceeds the first clinical breakpoint and pathogens that can grow in the presence of antibiotic concentrations above the second clini- cal breakpoint are referred to as resistant. The European committee on anti- microbial susceptibility testing (EUCAST) is working to update and unify clinical breakpoints throughout Europe.
To selectively kill bacterial cells while not harming host cells, clinically useful antibiotics must target essential bacterial pathways not present or
11
sufficiently different from those present in eukaryotic cells. Known targets involve: i) DNA replication, ii) RNA synthesis, iii) Protein synthesis, iv) The cell membrane, and v) Cell wall synthesis (Walsh and Walsh, 2003; Kohanski et al., 2010). DNA replication is inhibited by fluoroquinolones. These antibiotics induce DNA breaks and blockage of the DNA replication forks by inhibiting topoisomerase II and IV. Trimethoprim and sulfamethox- azole inhibit two essential enzymes in folic acid metabolism and thereby block nucleotide biosynthesis. Rifamycins bind to the β-subunit of the DNA- dependent RNA polymerase and inhibit RNA transcription. Inhibition of the ribosome impedes protein synthesis. Macrolides, lincosamides, strepto- gramins, amphenicols and oxazolidinones block the 50S ribosomal subunit and tetracyclines and aminoglycosides block the 30S ribosomal subunit. Antibiotics such as fosfomycin and bacitracin inhibit the synthesis of cell wall precursors. Cell wall biosynthesis is targeted by glycopeptides and β- lactams. Glycopeptides such as vancomycin bind to the D-alanyl-D-alanine peptidoglycan tail making it inaccessible for both transglycosylation and transpeptidation. β-lactams bind to the enzymes responsible for transpepti- dation, the transpeptidases, and form inactive enzyme complexes. This pre- vents effective peptidoglycan cross-linking. The focus of this thesis will be on β-lactams. Members of this potent class of antibiotics and their mode of action will be discussed in more detail in later chapters (Page 14).
Resistance to antibiotics In the environment microbes have evolved together for millions of years, releasing substances that serve to provide growth advantages over neigh- bouring microbes (among other functions). Consequently, microbial com- munities were exposed to naturally produced antibiotic substances long be- fore their clinical introduction. Resistance genes are thought to have evolved from enzymes with low binding affinity or moderate catalytic activity against an antibiotic, or originate from antibiotic producing bacteria. Studies have shown that the resistome (all antibiotic resistance genes and their pre- cursors in pathogenic and non-pathogenic bacteria) confers resistance to all known antibiotics, even those that environmental bacteria were never ex- posed to. It is even suggested that environmental organisms are by default drug resistant (Wright, 2007). This is threatening because genetic material can be transferred between organisms and species. The introduction of anti- biotics into clinical use conferred strong selective advantage to pathogens that were able to incorporate natural resistance genes into their genome.
DNA can be mobilized and transferred between organisms and species by horizontal gene transfer (HGT). HGT is proposed to be a major driving force in bacterial evolution and transformation, conjugation, transduction, and other mechanisms are known (Popa and Dagan, 2011). The uptake of DNA from the environment and its integration into the genome is called transfor-
12
mation. Some bacteria, for example Streptococcus pneumoniae are naturally competent and able to take up exogenous DNA (Johnsborg and Håvarstein, 2009). Conjugation is the process of DNA transfer via cell-to-cell contact. Here a so-called pilus from the donor cell establishes cell contact, initiating transfer of plasmid DNA or other mobile genetic elements (Frost and Koraimann, 2010; Wozniak and Waldor, 2010). The transfer of DNA be- tween viruses and bacteria is called transduction. Occasionally, bacterial viruses may package and transfer parts of the bacterial genome to a different cell. The potential for DNA mobilisation together with selective pressure from antibiotics in the environment and hospital settings, provide a strong possibility for the spread of resistance genes throughout microbial popula- tions.
Antibiotic resistance can also be acquired through de novo mutation of genes in the bacterial chromosome. Spontaneous mutations, such as nucleo- tide substitutions, frameshifts, deletions, inversions and amplifications, oc- cur as consequences of exogenous DNA damaging agents, endogenous agents (such as damaged bases), or DNA polymerase errors (Rosche and Foster, 2000). Efficient repair mechanisms have evolved to limit the number of spontaneous mutations, because the majority of mutations will be disad- vantageous and potentially lethal. These mechanism include the DNA poly- merase proofreading function, methyl-directed mismatch repair, the nucleo- tide excision repair systems, and various base excision repair systems and recombinational repair (Lindahl and Wood, 1999). For evolution to occur a certain amount of genetic diversity is needed, because in rare cases cells acquire beneficial mutations that confer a selective advantage over other cells in the population. In the presence of antibiotics, resistant mutants will be able to grow whereas sensitive cells will be inhibited or killed, leading to an enrichment of resistant cells in the population.
To date resistance to all available antibiotics can be observed in patho- genic bacteria. A main mechanism is the decreased uptake of antibiotics into the bacterial cell. Many small antibiotics, for instance β-lactams, enter the cell through water filled transport channels called porins (Pagès et al., 2008; Delcour, 2009). Decreases in the number of channels, changes of porin structure or expression of a different kind of porin (shift from general porins to specific porins, or from porins with wide diameter to porins with smaller diameter) can lead to resistance (Fernández and Hancock, 2012). After crossing the membrane, antibiotics and other toxic compounds can be recog- nized and exported out of the cell. Numerous transporters spanning the inner membrane or transporter complexes spanning both the inner and outer mem- brane can extrude antibiotics from the cytoplasm or periplasm (Piddock, 2006a; Piddock, 2006b). Furthermore, degradation or modification of the antibiotic can reduce the effective antibiotic concentration and lead to re- sistance and here hydrolysis of the β-lactam ring by β-lactamases is one of
13
the most important examples (Jacoby and Munoz-Price, 2005; Queenan and Bush, 2007; Livermore, 2008). Resistance can also be achieved by modifica- tion or replacement of the antibiotic target so it is not longer recognized by the drug (Hiramatsu et al., 2001; Lambert, 2005; Yamachika et al., 2013). More recently altered expression of target genes and amplification of re- sistance genes has been associated with resistance development (Sandegren and Andersson, 2009; Paulander et al., 2010).
Cost of resistance In the majority of cases mutations that confer resistance are associated with a cost in the absence of antibiotics. It is not always known which process confers the cost, and several processes may be involved simultaneously. One can imagine costs from changes in essential proteins that lead to lower pro- tein activity, from the use of the cell’s replication machinery to replicate resistance conferring plasmids, or from changes in the expression of regula- tory processes (Andersson and Levin, 1999; Andersson and Hughes, 2010). These costs can affect how well resistant bacteria are transmitted or cleared from the host, or affect their ability to compete with non-resistant cells. Costs are sometimes dependent on the environment and can vary with pH, temperature, osmolarity and nutrient availability. Thus, identifying fitness costs under standard laboratory conditions is not always straightforward, and repeated tests under a range of conditions may be required. Costs can be determined in different ways. For example, one can compare the maximum exponential growth rate of a mutant with that of the wild type. This gives valuable information about the growth potential of the mutant. Another more comprehensive method is to compete isogenic strains under different growth conditions, taking into account additional components, such as time spent in the lag phase, utilization of resources and survival during the stationary phase. Using technology such as flow cytometry and fluorescently labelled bacteria a large sample of bacterial population can be analysed, reducing experimental error and allowing the detection of differences in fitness costs as low as 0.3% (Lind et al., 2010). Competition of isogenic strains in exper- imental animals such as mice would represent an environment closer to that present in the human host, but this method is ethically questionable.
In addition, resistance mechanisms may also come with a low cost, none at all or even confer a fitness benefit (Luo et al., 2005; Ramadhan, 2005; Criswell et al., 2006; Kunz et al., 2012). However, in these cases it should be considered carefully, whether appropriate conditions were tested.
14
Can resistance be reversed? In an environment free of antibiotic selection pressure, fitness costs present growth disadvantages for resistant mutants and they are typically outcom- peted by non-resistant strains. However, subsequent compensatory mutations are readily selected and can decrease the cost associated with resistance. The resistance phenotype might be lost during the process of acquiring fitness compensating mutations. However, compensatory mutations often arise in different regions of the chromosome and both resistance and compensatory mutation can be present in the evolved strain. The combination of both mu- tations might make reversion of resistance genetically disadvantageous, be- cause the compensatory mutation alone may now confer a fitness cost. Also, several resistance conferring mechanisms can be acquired together, on plas- mids or other transferable elements and are then genetically linked. Given selection pressure for one of the linked resistance genes and depending on linkage distance, they can be co-selected and resistance will not be lost. Ad- ditionally, it has been demonstrated that the environment is often not antibi- otic free, but that low levels of antibiotics are present (Kümmerer, 2009). Contamination with antibiotics result not just from use of antibiotics as hu- man medication, but also from their widespread veterinary and agricultural application (Aarestrup, 2005; Cabello, 2006). Alarmingly, resistance muta- tions can be selected for at these low levels and already existing mutants are able to outcompete wild type bacteria…